Clinical Value of Combined Detection of UA and MMP-9 in Evaluating Bleeding Transformation and Prognosis After Thrombolysis in Acute Cerebral Infarction.

This paper presents an in-depth study and analysis of the assessment of hemorrhagic transformation and prognostic outcome after thrombolysis in acute cerebral infarction using a combined test and evaluates its clinical value. The ischemic tissue hemodynamic changes were compared and analyzed by the combined application of magnetic resonance conventional examination. Single-factor and multi-factor Logistic regression analysis was applied to the model group samples to determine the independent influencing factors of hemorrhage and to construct a risk prediction model. The Hosmer-Lemeshow chi-square test was used to test the fit of the model, and the area under the ROC curve was used to test the discriminatory ability of the model. The area under the ROC curve was used to test the discriminatory ability of the model. The main purpose of this study was to investigate the clinical diagnostic value of the combined D-D and Hcy and test for the early detection of patients with acute cerebral infarction disease. There was no significant correlation between single PWI-ASPECTS and clinical prognostic MRS score, which may be related to the site and volume of initial diffusion restriction; the percentage of the mismatched area between DWI-PWI and clinical prognostic mRS score was significantly correlated, which helps clinicians to assess the therapeutic effect of non-thrombolytic therapy and provide an important basis for clinical selection of appropriate interventions in the subacute phase of stroke. The sensitivity of D-D, Hcy, and cTnI in the acute cerebral infarction group was 59.4%, 79.6%, and 49.5%, and the specificity was 73.5%, 70.5%, and 91.1%, respectively, with the area under the curve of 0.606, 0.729, and 0.521. The sensitivity, specificity, and area under the curve of the combined assay were higher than those of the single assay. The detection level of high-risk group was the highest, followed by the low-risk group. Pearson correlation analysis suggests that there is a significant correlation between serum UA and MM-9 level and grace score.

Protein-drug interactome analysis of SSRI-mediated neurorecovery following stroke.

Serotonin selective reuptake inhibitors (SSRIs) have been widely used as first-line drugs in the treatment of a range of depressive and anxiety disorders. Recently, clinical studies found that this class of agents also shows significant efficacy in promoting neurogenesis, neuroplasticity and neurorecovery following stroke. Here, we attempt to elucidate molecular mechanism and biological implication underlying the SSRI-mediated neurorecovery. In the procedure, a comprehensive protein-drug interactome (PDI) was constructed for various SSRIs and their major metabolites as well as a group of control drugs across a large panel of human neuroproteins via a high-throughput molecular docking approach. The obtained PDI was then analyzed at systematic level to extract unexpected targets for SSRIs/metabolites. Biological network analysis and gene ontology (GO) enrichment solidified that the inferred targets have high potential to be directly or indirectly involved in diverse neural events, and further molecular dynamics (MD) simulation and post molecular mechanics-Poisson Boltzmann/surface area (MM-PB/SA) characterization revealed a stable complex architecture and high-affinity interaction between the targets and SSRIs/metabolites. Specifically, two human proteins, i.e. neurogenic locus notch homolog protein 1 (NOTCH 1) and Rho-associated protein kinase 1 (ROCK 1), were suggested as promising regulators in the SSRI-mediated neurorecovery, which can be targeted efficiently by fluoxetine and paroxetine, respectively, as well as other SSRIs and metabolites.